Week 9 Snaps Report

Week 9 Snaps Report

The Week 9 Snaps Report gives fantasy players a view into the Team’s system, positional usages, and player activities. Does the team use RBs more than WRs? Does the team rely on their WRs? These are key questions for lineups, DFS plays, and waiver wire selections. These metrics strengthen as the season goes on. Please come back and continue following my work!

==================================================

Landscape Data Informatics for my

Week 9 Snaps Report

I believe one way to fight the various biases we as Fantasy Players have to deal with is to use landscape metrics. This prevents the more common “Silo Effect” most “experts” deal out.

Not only is fantasy a weekly game it is a complex system. System-level predictions are tough.  However, innovation often comes from combining data from several sources. I interpret this as a call for fantasy players to use multi data approaches for this game. See the link for starting your exploring. 

make-better-decisions-combine-datasets

Consider the landscape views of multi-data veins that invite mining for informatic gold. This is my journey within Fantasy in a nutshell! I wish to “show” others my approaches as well.

==================================================

Team Average Snaps Week 1 to 9

As we have 9 weeks of data for the teams, I wanted to up the game here by combining multi-data sources and use ratio metrics for hypothesis formation. I begin by the landscape view. More Snaps associate with team speeds. Fast Teams are more passing centric vs slower snaps teams are rushing heavy. (Data from my textbook studies). You should assume the level of pass vs run is based here on team speeds **. 

I colorized the team names (Green to Red) based on the weekly team snaps (Purple to Yellow).  I also present the overall snaps average (green to red) and snaps scaled to average (blue to red). Scaled metrics visually give you an impact value of the metric!

Late vs Early Snap Averages 

These data also give a view of the entire season (LATE vs EARLY first 9 weeks) in Team SNAPS Teams that are getting faster may be winning more in the next upcoming games vs slowing down and losing more.

Additionally, the LATE vs EARLY metric catches this big turn.

TB/HOU/DAL/NO/MIN have sped up in Snap based Team Speed.

BAL/LAR/BUF/ARI/WAS/KC have slowed down. 

What teams are speeding up or slowing down? The number of SNAPs can point to rushing vs passing Team Biases (Following FIgure). Additionally,  I watch for team trend shifts to trade, drop, or acquire players. These metrics pinpoint various time frames of Team Snaps. Weekly Snaps will have a variation that can hide the bigger trends.

Key into these larger trends. Watch for player changes that may have fueled this metric. FYI there may be some association with SNAP Speed and Losing Games. 

Slide1

==================================================

TEAM SNAP AVERAGES vs Team Rushing vs Passing%

Is there a connection to team snaps and a team’s style of offensive? Most pundits dwell at the player level but I practice a TOP down approach because I think it allows players to set the landscape for their decisions.

The distribution of Team Biases either Rushing or Passing is shown vs the Top to Bottom of a Team Snap averages. Yes, it appears that a team’s Snap average can be used to associate a style of play. Nearly 50% of rushing based teams are within the top 10 teams in snaps (7 out of 10). More Snaps more rushing.

Interestingly, fewer snaps point to passing based activity and are found in those lower SNAP average teams (80% of the bottom teams are passing based teams). See the Bar-Graph for the trends of Rushing and Passing crisscrossing across the HIGH VS Low Team Snaps.

Use to formulate DFS and Lineups vs Vegas Lines, Defense Metrics and my rankings. 

Slide2

==================================================

Team Positional Level of Average Team Snaps and DIFFs

I always suggest players use a broad view of a Team’s activities. I continue in this Snap Report by looking at the positions. Note, all metrics are colorized High to Low.

These tables from the Week 8 Snaps Report include:

  • Team
  • Position
  • Week 1 to 9 Snaps
  • Average of Player Snaps Per Week
  • % Team Snaps (%TS) 
  • Late vs Early Snap Average Changes (Stars highlight extremes)
  • Bar Graph of the Positional Usages

These tables focus on the position level of each team. I suggest positional snap averages give a nice distribution of snaps to begin an understanding of Team positional usages. Playing players from low vs high positional usages can win or lose a DFS play for this week’s matchup. 

You must go through these figures a few times and focus on the extremes. As I tell my students that there is a Big Difference with being familiar with vs knowing. Move toward knowing. Next year maybe write an essay on each team for 2020.

For Example ARI TEs not used! 25% is weak! Bal RBs are underused at 24% but love its TEs at 39%! Find these keys to unlock your plays!

==================================================

ARI_ATL_BAL_BUF 

Slide4

Slide5

==================================================

CAR_CHI_CIN_CLE

Slide6

Slide7

==================================================

DAL_DEN_DET_GB

Slide8

Slide9

==================================================

HOU_IND_JAX_KC

Slide10

Slide11

==================================================

LAC_LAR_MIA_MIN

Slide12

Slide13

==================================================

NE_NO_NYG_NYJ

Slide14

Slide15

==================================================

OAK_PHI_PIT_SEA

Slide16

Slide17

==================================================

SF_TB_TEN_WAS

Slide18

Slide19

==================================================

Team Snap Based Positional Usages 

Use these usages %TS as a way of thinking about how a team is operating. I find the extremes and use that data to move toward or away from players. I will let users scan the data and decide what key facts are germane to your teams. Find your own connections. Good tiebreaker as well. 

Note the teams that have success using in their distributions. Are the snaps because of poor play etc or deliberate to winning? Deeper questioning! All Positions include weeks 1 to 9 average snaps, a grand 9-week average, and a Team Snap %. I sorted High %TS to Low.  The colorization allows the focus on the extremes especially in the Late vs Early Differences. 

==================================================

 

Running Backs

Suggest you focus your handcuffs on the high use teams. Caution on DET pickups this week! Det is the 3rd worst RB usage team. KC is also an issue in RBs usages. Watch for changes! 

Slide21


CIN/NO/CLE all have high RB usages with recent improvements. Watch!

ARI/LAR/CAR all have high RB usage but recent large declines.

Slide22

==================================================

Tight Ends

Slide24

Nice that the top 4 TE using Teams have should improvements as well in recent weeks! Double down on these TEs? PHI/HOU/NE/MIN

Slide25

==================================================

Wide Receivers

Slide27

Nice CLE/CIN/TB high WRs usages and improvements

DET/DAL/LAR/CAR/CHI are all high WR users but have declined recently. Caution.

Slide28

==================================================

Player Snaps Within Teams Weekly and Snap Averages -Environment Analysis. 

The following tables present the player Snaps in their position within Teams, Weeks 1 to 9 Snaps and their grand Snap Averages. I colorized the Snaps within each team. This colorization allows a scan across and down the players and positions. 

I added player SNAP Share metrics (% Team Snaps -%TS) to “see” the season so far. These metrics capture the Team usage of all players. Watch for changes but use these Snap Shares as a foundation of your analysis. 

Additionally, I use the deeper Team Player Snaps environment analysis for my lineups in seasonal and DFS as well as drop adds, handcuffs identification and previous week game scripts for positions usages. I look for upcoming late-season blooming players.

I really suggest you finalize your teams by week 10 to 12 going into the playoffs. Use this data to help formula your trades and acquisitions. 

==================================================

Slide30

Slide31

Slide32

Slide33

Slide34

Slide35

Slide36

Slide37

Slide38

Slide39

Slide40

Slide41

Slide42

Slide43

Slide44

Slide45

Slide46

Slide47

Slide48

Slide49

Slide50

Slide51

Slide52

Slide53

Slide54

Slide55

Slide56

Slide57

Slide58

Slide59

Week 9 Snaps Report Slide60

Week 9 Snaps Report Slide61

==================================================

 Player by Team Positional Snap Use (Week, Average, %TS, DIFF, and Late vs Early)

I sorted the players from high team usage (%TS) purple to low team usage yellow. Use the Late vs Early DIFF to focus on recent changes in increases or decreases in Snaps. 

================================================== 

Running Back

Slide63

Slide64

Slide65

Slide66

Slide67

Slide68

==================================================

Tight Ends 

Week 9 Snaps Report Slide70

Week 9 Snaps Report Slide71

Week 9 Snaps Report Slide72

Week 9 Snaps Report Slide73

Week 9 Snaps Report Slide74

==================================================

Wide Receivers 

Slide76

Week 9 Snaps Report Slide77

Week 9 Snaps Report Slide78

Week 9 Snaps Report Slide79

Week 9 Snaps Report Slide80

Week 9 Snaps Report Slide81

Week 9 Snaps Report Slide82

Week 9 Snaps Report Slide83


Please use SNAP data with my Rankings this week.

Fantasy-Football-Week-10-Rankings

Leave a Reply

This site uses Akismet to reduce spam. Learn how your comment data is processed.

%d bloggers like this: